End-of-Chapter Application Case Why is beer flavor important to Coors’ profitability?What is the objective of the neural network used at Coors?Why were the results of Coors’ neural network initially poor, and what was done to improve the results?What benefits might Coors derive if this project is successful?What modifications would you make to improve the results of beer flavor prediction?

The beer flavor is important to the Coors' profitability because of the following: Decision on…

Answered: End-of-Chapter Application Case Why…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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End-of-Chapter Application Case
- Why is beer flavor important to Coors’ profitability?
- What is the objective of the neural network used at Coors?
- Why were the results of Coors’ neural network initially poor, and what was done to improve the results?
- What benefits might Coors derive if this project is successful?
- What modifications would you make to improve the results of beer flavor prediction?

Expert Solution

Step 1

The beer flavor is important to the Coors' profitability because of the following:
Decision on customer relies on different variables.
It could have the streets open when the end of the goal is to make the customer's happy and contended.
The main objective is it has to be linked with the input as well as the outputs which in turn can lead to the balanced objective analytical as well as more subjective sensory.
Every individual has his own taste and flavor according to the occasions Coors' belief was that the company should understand about the beer flavor solely based on its chemical composition.
They were concentrating only on single products quality where variation of data was very low. because of low quality of data neural network was in a position to extract useful relationship from existing data.
only subset of the provided input had impact on beer flavor that had no impact on the neural network instead was affected by noise .

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